Radiation Dose Estimation via Synthetic Image Comparison
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Solution Overview
Problem
In radiation therapy, there is a need to accurately measure the actual dose delivered to a patient, as it often differs from the planned dose due to factors like patient setup and motion, necessitating systems and methods for precise dosimetry.
Innovation Solution
A system and method that utilize a processor to obtain beam and detector models, reference images, and treatment plans, determining synthetic and treatment images, scaling factors, and estimating radiation dose deposition to detect errors in radiation therapy by comparing ratios and differences between these images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If radiation therapy treatment is delivered according to a planned treatment plan, then the treatment can be completed efficiently, but the actual dose delivered may differ from the planned dose due to patient setup and motion errors
Solution Approach 1:
The system performs preliminary actions by acquiring patient anatomy images (CT, MRI, or ultrasound) before treatment delivery and using these images to calculate expected detector responses under various setup conditions. This allows the system to prepare a library of predicted images that can be quickly compared against actual treatment images to detect setup errors and estimate actual dose delivery without interrupting the treatment workflow.
Solution Approach 2:
The system creates synthetic copies of expected treatment images by simulating detector responses based on the treatment plan and patient anatomy. These synthetic images serve as reference models that can be compared against actual treatment images. The copying approach allows error detection and dose estimation without requiring additional physical measurements during treatment, maintaining efficiency while improving accuracy.
2Measurement precision
If the system compares actual treatment images with synthetic images to detect setup errors and estimate dose, then measurement precision improves, but device complexity increases due to multiple image processing steps
Solution Approach 1:
The detector system serves multiple functions: it acts as both a treatment verification device by capturing actual treatment images and as a dosimetry device by comparing these images with synthetic references to estimate dose delivery. This multi-functionality allows the system to perform error detection and dose estimation using existing infrastructure, reducing the need for separate complex measurement systems while improving measurement precision.
Solution Approach 2:
The system replaces complex physical dosimetry measurements with computational image analysis. Instead of using additional physical detectors or measurement devices during treatment, the system uses computational methods to compare actual treatment images with synthetic images generated from treatment plans and patient anatomy, substituting mechanical measurement systems with information processing approaches.
3Measurement precision
If the system uses patient-specific anatomy images to calculate expected detector responses, then measurement precision improves, but the time required for treatment preparation increases
Solution Approach 1:
The system performs preliminary calculations of expected detector responses using patient-specific anatomy images acquired before treatment. By completing these computationally intensive tasks in advance, the system prepares all necessary reference data and synthetic images before treatment delivery begins, allowing rapid error detection and dose estimation during treatment without adding significant preparation time.
Solution Approach 2:
The system dynamically adapts the level of detail in synthetic image generation based on treatment requirements. For routine treatments, simplified synthetic images may suffice, while for more complex cases requiring high precision, more detailed calculations are performed. This dynamic approach allows the system to balance measurement precision with preparation time requirements on a case-by-case basis.
Data Source
AI summary
The present disclosure provides a system and method for dose measurement in radiation therapy. The method may include obtaining a beam model and a detector model related to a radiation device, and a reference image and a treatment plan related to the subject, and determining a synthetic image based on the beam model, the detector model, and the reference image. The method may also include obtaining a treatment image by performing at least a portion of the treatment plan including delivering at least a radiation beam toward the subject using the radiation device, and determining one or more scaling factors. The method may further include determining a synthetic estimate of the treatment image based on the synthetic image and the one or more scaling factors. The method may further include estimating radiation dose deposition based on the treatment image and the synthetic estimate of the treatment image.